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{"id": "cc-by-4.0",

"name": "Creative-Commons - Attribution 4.0 International (CC BY 4.0)",

"url": " http://dcat-ap.de/def/licenses/cc-by/4.0 ",

"quelle": "Copyright DLR (2022)"}

This dataset provides large-scale information on vegetation structure information (canopy height, total canopy cover, plant area index, foliage height diversity index), that allows for a complete understanding of spatial characteristics for the complete Paraguayan Chaco, when combined with the other modelled data sets.

Geo-ForPy - Forest Structure Information for the Paraguayan Chaco - Processing

Data:

The data basis for modelling comprises data from Synthetic-Aperture-Radar (SAR) from Sentinel-1, multispectral Information from Sentinel-2 and LiDAR (Light detection and ranging) data from GEDI. All data has been filtered to the period of the dry season 2019 (April to September).

Processing:

GEDI data has been preprocessed (quality and temporal filtering) on a local machine (16 GB RAM). Sentinel preprocessing (Sentinel-1: radiometric terrain normalization and speckle filtering; Sentinel-2 cloud masking, vegetation indices, temporal-spectral metrics) and modelling has been fully conducted in Google Earth Engine using the Python API.

Quality Assurance:

Cover: Modeling accuracy for total canopy cover amounts to: 61.4 % in R² (coefficient of determination) and 9.1 % in RMSE (root mean square error).

Fhdi: Modeling accuracy for Foliage height diversity index amounts to: 48,0 % in R² (coefficient of determination) and 0,3 in RMSE (root mean square error).

Pai: Modeling accuracy for Plant area index amounts to: 50,6 % in R² (coefficient of determination) and 0,3 in RMSE (root mean square error).

rh95 Modeling accuracy for canopy height amounts to: 64,0 % in R² (coefficient of determination) and 1,6 m in RMSE (root mean square error).